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Xin Liao and Khoi D. Hoang
Distributed Constraint Optimization Problems (DCOPs) are an efficient framework widely used in multi-agent collaborative modeling. The traditional DCOP framework assumes that variables are discrete and constraint utilities are represented in tabular form...
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Libero Nigro and Franco Cicirelli
K-Means is a ?de facto? standard clustering algorithm due to its simplicity and efficiency. K-Means, though, strongly depends on the initialization of the centroids (seeding method) and often gets stuck in a local sub-optimal solution. K-Means, in fact, ...
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Gauri Vaidya, Meghana Kshirsagar and Conor Ryan
Neural networks have revolutionised the way we approach problem solving across multiple domains; however, their effective design and efficient use of computational resources is still a challenging task. One of the most important factors influencing this ...
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Liliya A. Demidova and Artyom V. Gorchakov
The massive nature of modern university programming courses increases the burden on academic workers. The Digital Teaching Assistant (DTA) system addresses this issue by automating unique programming exercise generation and checking, and provides means f...
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Jeffrey O. Agushaka and Absalom E. Ezugwu
A situation where the set of initial solutions lies near the position of the true optimality (most favourable or desirable solution) by chance can increase the probability of finding the true optimality and significantly reduce the search efforts. In opt...
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Milad Showkatbakhsh and Mohammed Makki
The complexity associated with the design of urban tissues is driven by the multitude of design goals that influence urban development and growth. This complexity is amplified by the design goals being inherently conflicting, necessitating preference-bas...
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Aleksei Vakhnin and Evgenii Sopov
Unconstrained continuous large-scale global optimization (LSGO) is still a challenging task for a wide range of modern metaheuristic approaches. A cooperative coevolution approach is a good tool for increasing the performance of an evolutionary algorithm...
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Zhenglong Li and Vincent Tam
Meta-heuristic algorithms have successfully solved many real-world problems in recent years. Inspired by different natural phenomena, the algorithms with special search mechanisms can be good at tackling certain problems. However, they may fail to solve ...
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Christoph Tholen, Tarek A. El-Mihoub, Lars Nolle and Oliver Zielinski
In this study, a set of different search strategies for locating submarine groundwater discharge (SGD) are investigated. This set includes pre-defined path planning (PPP), adapted random walk (RW), particle swarm optimisation (PSO), inertia Levy-flight (...
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Mohammad Dehghani, Zeinab Montazeri, Ali Dehghani, Om P. Malik, Ruben Morales-Menendez, Gaurav Dhiman, Nima Nouri, Ali Ehsanifar, Josep M. Guerrero and Ricardo A. Ramirez-Mendoza
One of the most powerful tools for solving optimization problems is optimization algorithms (inspired by nature) based on populations. These algorithms provide a solution to a problem by randomly searching in the search space. The design?s central idea i...
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